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Questions tagged [game-ai]

For artificial intelligence questions related specifically to games.

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My iterative deepening engine doesn't have an exactly equal score when playing against itself

I made a Connect Four engine that uses the standard minimax/alpha-beta algorithms as its underlying structure, with iterative deepening added on. Because the engine uses iterative deepening, its ...
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0answers
14 views

Why does Q-learning converges to optimal policy even if I am acting suboptimally?

In Q-learning, during training, it doesn’t matter how I select actions. The algorithm always converges to optimal optimal policy. Why does this happen?
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1answer
21 views

Is it possible to use a feed-forward neural network to predict the actions in reinforcement learning?

I have done a lot of research on the internet about Reinforcement Learning and I found encountered methods of Reinforcement Learning: Q-Learning and Deep Q-Learning. And I have developed a vague idea ...
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15 views

What Actually is Off-Policy Q-Learning?

Recently I have come across an information stating: Q-learning converges to optimal policy -- even if you’re acting suboptimally! It also states: When an optimal policy is still learned from ...
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20 views

How to model a plumber dispatcher with Artificial Intelligence?

The domain of emergency call for clogged pipelines has to do with taking a call and managing the reaction of plumber departments. It is mostly a group oriented communication situation between the ...
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0answers
18 views

How to use Genetic Algorithm for varying lengths of solutions

Until now, I always thought that Genetic Algorithm can be used for problems of which the solution space can be encoded (modeled) as a chromosome of a specific length. However, some people claim that ...
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1answer
31 views

How do I know how changes in the weights are changing the reward in Reinforcement Learning

I already know the basics of the basic of Machine Learning. E.g.: Backpropagation, Convolution, etc. First of let me explain Reinforcement learning to make sure I grasped the concept correctly. In ...
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20 views

Checkers AI game engines

I have coded an AI checkers game but would like to see how good it is. Some people have informed me to use the Chinook AI opensource code. But I am having trouble trying to integrate that software ...
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1answer
33 views

Transposition table is only used for roughly 17% of the nodes - is this expected?

I'm making a Connect Four game using the typical minimax + alpha-beta pruning algorithms. I just implemented a Transposition Table, but my tests tell me the TT only helps 17% of the time. By this I ...
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1answer
27 views

Is it meaningful to give more weight to the result of monte carlo search with less turn win?

I'm programming on Connect6 with MCTS. Monte Carlo Tree Search is based on random moves. It counts up the number of wins in certain moves. (Whether it wins in 3 turns or 30 turns) Is the move with ...
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1answer
35 views

What's the difference between poker with public cards and without them?

Example: texas holdem poker vs texas holdem poker with the same rounds, just with no public cards dealt. Would algorithms like CFR approximate Nash-equilibrium more easily? Could AI that does not ...
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1answer
31 views

Using a DQN with a variable amount of Valid Moves per turn for a Board Game

I have created a game on an 8x8 grid and there are 4 pieces which can move essentially like checkers pieces (Forward left or Forward right only). I have implemented a DQN in order to pull this off. ...
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2answers
109 views

Creating a self learning Mario Kart game AI?

I will be undertaking a project over the next year to create a self learning AI to play a racing game, currently the game will be Mario Kart 64. I have a few questions which will hopefully help me ...
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0answers
22 views

How does using neural network to improve evaluation function work?

I’ve seen some papers using neural network as evaluation function to evaluate game state. I wonder if they can value the state to train the neural network, isn’t the function that is used to value the ...
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1answer
30 views

Connect 4 minimax does not make the best move

I'm trying to implement an algorithm that would choose the optimal next move for the game of Connect 4. As I just want to make sure that the basic minimax works correctly, I am actually testing it ...
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1answer
167 views

Does a solution for Wumpus World with neural networks exist?

The Wumpus World proposed in book of Stuart Russel and Peter Norvig, is a game which happens on a 4x4 board and the objective is to grab the gold and avoiding the threats that can kill you. The rules ...
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0answers
32 views

Mapping Actions to the Output Layer in Keras Model for a Board Game

I have created a game based on this game here. I am attempting to use Deep Q Learning to do this, and this is my first foray into Neural networks (please be gentle!!) I am trying to create a NN that ...
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3answers
58 views

Can genetic algorithms be used to learn to play multiple games of the same type?

Is it possible for a genetic algorithm + Neural Network that is used to learn to play one game such as a platform game able to be applied to another different game of the same genre. So for example, ...
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1answer
70 views

Should Q values be changing within an epoch/episode or should they change after one episode/epoch?

I am trying to use Deep-Q learning environment to learn Super Mario Bros. The implementation is on Github. I have a neural network that Q values update within an episode for a very small learning ...
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1answer
34 views

Historical weakness of GOFAI in relation to partisan combinatorial games?

I was recently perusing the paper Some Studies in Machine Learning Using the Game of Checkers II--Recent Progress (A.L. Samuel, 1967), which is interesting historically. I was looking at this figure, ...
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1answer
70 views

Algorithms for games with very high branching factors (Connect6)

Connect6 is an example of a game with a very high branching factor. It is about 45 thousand, dwarfing even the impressive Go. What algorithms can you use on games with such high branching factors? I ...
3
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1answer
88 views

Monte Carlo Tree Search Expansion Phase

I'm confused regarding a specific detail of MCTS. To illustrate my question, lets take the simple example of tic-tac-toe. After the selection phase, when a leaf node is reached, the tree is expanded ...
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2answers
125 views

How to go forward with creating an artifically intelligent aimbot for a game like CS:GO

Artificial Intelligence can be realized as a full autonomous or as a semi-autonomous system. A full autonomous system takes the human operator out of the loop, his hands are away from keyboard and he ...
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0answers
30 views

Open Ai Gym states become corrupt?

I'm trying to implement a3c for flappy bird using this code https://github.com/awjuliani/DeepRL-Agents/blob/master/A3C-Doom.ipynb. It works perfectly well but what I noticed is that when I save the ...
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0answers
57 views

Evolving network in game

So I wrote simple feed forward neural network that plays tic-tac-toe: 9 neurons in input layers: 1 - my sign, -1 - opponent's sign, 0 - empty; 9 neurons in hidden layer: value calculated using Relu; ...
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1answer
65 views

Can you analyse a neural network to determine good states?

I've developed a neural network that can play a card game. I now want to use it to create decks for the game. My first thought would be to run a lot of games with random decks and use some ...
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2answers
69 views

Are there any discount-factors based on branching factors?

I recently came across this function: $$\sum_{t = 0}^{\infty} \gamma^t R_t.$$ It's elegant and looks to be useful in the type of deterministic, perfect-information, finite models I'm working with. ...
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2answers
82 views

More effective way to improve the heuristics of an AI… evolution or testing between thousands of pre-determined sets of heuristics?

I'm making a Connect Four game where my engine uses Minimax with Alpha-Beta pruning to search. Since Alpha-Beta pruning is much more effective when it looks at the best moves first (since then it can ...
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2answers
84 views

Does Monte Carlo Search (specifically used by AlphaZero) Qualify as Machine Learning?

To the best of my understanding, Monte Carlo Search is an alternative method to Minimax for searching a tree of nodes. It works by choosing a move (generally the one with the highest chance of being ...
4
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1answer
84 views

Algorithm For Making Balanced Weapons In A Game?

I am trying to make balanced weapon pairs. So there are five stats per weapon, and I am simulating a number of combats (1000) with different stats randomized, and counting the win, lose, and draw of ...
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1answer
42 views

Quiescence search

Games like checkers have compulsory moves. In checkers for instance, if there's a jump available a player must take it over any non-jumping move. My question is, if jumps are compulsory will there ...
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2answers
39 views

Is an evaluation function as good as an optimization function

I have been so for self-learning basic A.I concepts and would like to know if having a really good evaluation function as good as any of alpha-beta pruning optimization functions such as killer moves, ...
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1answer
85 views

Alpha-beta pruning algorithms optimizations

I know that they are quite alot of optimizations for alpha-beta pruning but what does it mean exactly: 1) Does it mean that these optimized algorithms are to be integrated into the alpha-beta ...
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1answer
90 views

Mathematical modelling of A.I algorithms

How does one even begin to mathematically model an A.I algorithm like alpha-beta pruning or even its thousands of variations, to determine which variation is best?
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4answers
182 views

What if there's a game where all the AI people actually lived?

Imagine the fictitious scenario in a role playing game (RPG) where the non-playing characters (NPCs) within the RPG are conscious of their own surrounding and consider the developer to be god. The ...
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1answer
81 views

Which is more memory efficient uninformed or informed search algorithms?

I have extensively researched now for three days straight trying to find which algorithm is better in terms of which algorithm uses up more memory. I know uninformed algorithms like depth-first search ...
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1answer
70 views

Why was Go a harder game for an AI to master than Chess?

AI became superior to the best human players in chess around 20 years ago (when the 2nd Deep Blue match concluded). However, it took until 2016 for an AI to beat the Go world chess champion, and this ...
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5answers
2k views

How do I choose which algorithm is best for something like a checkers board game?

I am currently new to artificial intelligence but I am very intrigued by it. I am currently researching three algorithms, namely: Minimax, Alpha-beta pruning and Monte Carlo tree search. As you may ...
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1answer
110 views

Representing inputs and outputs for a card game neural network

I'm attempting to create an AI for a card game using reinforcement learning. The basics of the game are that you can have (theoretically) up to 35 cards in your hand, you can also have to up to 35 ...
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1answer
59 views

How to use Machine Learning with simple games?

I built a simple HTML game. In this game the goal is to click when the blue ball is above the red ball. If you hit, you get 1 point, if you miss, you lose 1 point. With each hit, the blue ball moves ...
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3answers
535 views

Why does Monte Carlo work when a real opponent's behavior may not be random

I am learning about Monte Carlo algorithms and struggling to understand the following: If simulations are based on random moves, how can the modeling of the opponent's behavior work well? For ...
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0answers
142 views

Reinforcement Learning in Commercial Strategy Games

I'm a professional game developer investigating the potential for using reinforcement learning to build strategy game AI opponents that have more creative behavior compared to traditional techniques ...
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1answer
138 views

Issue with simple game AI

A few months ago I made a simple game that is similar to the dinosaur game in Google Chrome - you jump over obstacles, or don't jump over levitating obstacles, and jump to collect bitcoins, which can ...
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1answer
36 views

Teaching a NN to manipulate pseudoRNG over a long time scale?

For speedrunning purposes, I am trying to train a neural network to identify human-executable ways to manipulate pseudo-RNG (in Pokemon Red, for the interested). The game runs at sixty frames per ...
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1answer
190 views

Genetic Algorithm - creatures in 2d world are not learning

Goal - I am trying to implement a genetic algorithm to optimise the fitness of a species of creatures in a simulated two-dimensional world. The world contains edible foods, placed at random, and a ...
2
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1answer
117 views

How to handle varying types and length of inputs in a neural network?

After learning the basics of neural networks and coding one working with the MNIST dataset, I wanted to go to the next step by making one which is able to play a game. I wanted to make it work on a ...
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2answers
87 views

Developing an AI to play outdoor games

I was wondering if it is possible to train an AI that can play outdoor games like cricket, badminton etc. I am new to AI, so if this question is dumb please bear it.
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2answers
65 views

Developing character tactics via repeated trials

Let's assume a common game scenario of several characters in a combat arena. Each character has different strengths and weaknesses. The arena has traps and tools. Suppose the characters had only very ...
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1answer
399 views

Training AI to play NES/SNES games on NN python

I am currently getting into Deep Learning and would like to set up an environment for training an Artificial Neural Network or NEAT to play simple video games on NES (Mario etc.) and SNES ( Donkey ...
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1answer
57 views

Which edges of this tree will be pruned by Alpha-beta pruning?

So I know that 'h' and 'f' will be pruned, but I'm not sure about 'k' and 'l'. When we visit 'j', technically there is no need for us to visit 'k' and 'l' because there are 2 options: one or two of ...